Why AI is rocket fuel for DevOps

Advanced automation frees up developers for strategic work

By Bob Violino

DevOps is an early test case for the potential of AI to
separate tech leaders and laggards

Top‑performing DevOps
teams automate functions like testing and spend more time building
new features

Automating these tasks allow developers to act
more like business consultants

To understand how artificial intelligence will widen the gap between
top‑performing IT teams and the rest of the field, take a look at
DevOps, the software development methodology that many IT leaders now
swear by.

While DevOps teams have used automation tools in software testing
for years, recent advances in machine learning and AI are yielding
significant gains in productivity and efficiency.

The highest‑performing DevOps organizations, measured by factors
like deployment frequency and change failure rates, have fully
embraced AI tools and automated 72% of their development processes,
according to a 2017 Puppet survey of over 3,200 DevOps professionals.

These top performers do significantly less manual work than low
performers. The survey found that compared to laggards, DevOps leaders
have automated 33% more of their configuration management, 27% more of
their testing, 30% more of their deployments; and 27% more change
approval processes.

By integrating AI into DevOps, these forward‑thinking companies
aren’t just accelerating production cycles and catching product bugs
and security flaws earlier. They’re empowering developers to expand
their skills and assume valuable new roles.

When DevOps met AI

Since it first emerged a decade or so ago, DevOps has offered a new
approach to software development, one based on intense collaboration
between developer and operations teams in order to build, test and
release software at far faster rates than was possible in previous years.

Tech bellwethers like Amazon, Google, and Netflix were early DevOps
disciples. Now thousands of other companies, including American
Airlines, Hertz, and Nordstrom, have adopted the practice. In a 2017
Forrester survey of
software developers, 90% reported that their companies were using
DevOps in some form, or have plans to start.

The benefits of automation to DevOps processes have been obvious from
the beginning, says Michael Azoff, principal analyst at research firm
Ovum. By eliminating manual steps, organizations can reduce human
error in app delivery while speeding up the development process.

In a CI process, code is integrated into a shared repository several
times a day with the goal of detecting problems. In a CD process, code
changes are automatically built, tested and prepared for release to production.

By using AI algorithms to automate both of these vital processes,
DevOps teams can test for potential bugs and security flaws early.
This speeds up product releases and frees developers to focus on more
strategic tasks.

At USA Today, for example, developer teams release 110 targeted
editions of the publication each day for more than a dozen mobile
devices. This required 588 separate UX tests managed by DevOps teams,
according to TechTarget.

Until last year, tests took 90 minutes to complete. But after USA
Today implemented an AI‑enabled testing platform for CI and CD, the
average test time shrank to less than ten minutes.

Similarly, when HP’s firmware division invested in automated testing
for its LaserJet 4, the DevOps teams were able to redeploy staff and
boost time spent developing new features sevenfold, according to the
Puppet report.

Schooled by AI

Nascent AI tools for software development are also changing how
schools teach young developers. At Holberton School in San Francisco,
students train to become full‑stack software engineers through
hands‑on, team‑based learning. AI tools are already an integral part
of the curriculum.

One reason for the shift: Most of Holberton’s teachers and mentors
are working industry professionals who are acutely aware of the
significance of AI‑powered automation for the future of DevOps.

“The idea behind these tools is to get machines to ‘self‑heal’
without human intervention,” says Kalache, the school’s co‑founder.
“The more data you have, the more you can predict the problem that
your infrastructure, service or server might have and how to
automatically fix it. AI and machine learning are at the heart of what
makes these tools efficient.”

Developers rising

One consequence of this new approach is that many developers are
taking on more strategic roles in their organizations.

“Developers are becoming more like business consultants—they sit
next to their product’s ends users and figure out what they really
want from the product,” says Torsten Volk, managing research director
of IT consulting firm Enterprise Management Associates. “A good
developer is one who understands the customer. The best developers are
those who listen the best.”

A growing trend that Volk points to is software vendors bringing
developers into their support centers to engage with customers.

What are customers’ frustrations? What would make the app work
better for their needs? Developers can use these insights to refine
existing features and dream up new ones.

Kalache finds that some IT roles are becoming obsolete. “Roles like
system administrator are becoming a thing of the past,” he says.
That’s because there is no longer a need for tasks such as capacity
planning and performing manual and repetitive work. “The new breed of
system administrators [are] automating themselves out of the job, so
that they can focus on innovation rather than operations.”

Developers who dabble in AI needn’t worry about job security if they
can upgrade their skills. “We used to hire developers with specialized
skills,” Volk says. “Now we hire full‑stack developers who do
everything from database to business processes to the presentation
layer—they understand the whole process. They understand the impact of
the software before they even start coding.”

The more AI frees DevOps teams from mundane tasks, the more it
empowers them to help companies outpace the competition in speed,
security and innovation.

Bob Violino, a former senior editor at InformationWeek, writes
about cloud computing, mobile technology, and other topics.